code: def df_regression():
      df = {
          "cat_var_A": ["A"] * 5 + ["B"] * 5 + ["C"] * 5 + ["D"] * 5,
          "cat_var_B": ["A"] * 6
          + ["B"] * 2
          + ["C"] * 2
          + ["B"] * 2
          + ["C"] * 2
          + ["D"] * 6,
          "num_var_A": [
              1,
              1,
              1,
              1,
              1,
              2,
              2,
              2,
              2,
              2,
              3,
              3,
              3,
              3,
              3,
              4,
              4,
              4,
              4,
              4,
          ],
          "num_var_B": [
              1,
              1,
              1,
              1,
              1,
              1,
              2,
              2,
              3,
              3,
              2,
              2,
              3,
              3,
              4,
              4,
              4,
              4,
              4,
              4,
          ],
      }
  
      df = pd.DataFrame(df)
      df = pd.concat([df, df, df, df], axis=0)
  
      y = pd.Series(
          [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3]
      )
      y = pd.concat([y, y, y, y], axis=0)
      return df, y
  
file_path: feature_engine/tests/test_selection/test_target_mean_selection.py
imports: import pandas
  import pytest
  from feature_engine.selection import SelectByTargetMeanPerformance
label_desc: Use image node_id 2 for calling a global function with example usage: df_regression() and returns: df,  y